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& Bioinformatics, is seeking candidates for a postdoctoral research fellow position. This is primarily for an NIH-funded project developing multimodal variational autoencoder models and probabilistic trajectory
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develop AI models to predict and study the tumor evolution and lineages using the multiomic measurements from both bulk, single-cell, and spatial technologies. The lab emphasizes understanding
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signal processing models to analyze waveforms generated by traditional patient monitors and a novel wearable sensor and build a decision support tool to guide CPR Participate in the user interface and
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. vector design and generation, genetic murine models, and/or genome editing), a strong understanding of physiology and disease models, as well as a track record of innovative scientific contributions
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resistance, utilizing human and murine cells, orthotopic models, and Genetically Engineered Mouse Models (GEMMs). We are seeking a motivated and hard-working scientist with strong project leadership and
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recruiting a post-doctoral researcher to develop computational models to study the spatial organization and microenvironment interactions in tumors using spatial multiomic data. The lab focuses on mathematical
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Required Qualifications* PhD degree in bioinformatics Minimum 1 year of relevant experience Hands-on experience with R and/or Python and performing independent computational modeling. Ability to maintain
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system near 1.9 microns. In both projects, the successful applicant will be responsible for synthesizing modeling and experimental data analysis and drafting high-quality manuscripts for publication
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, biomedical engineering, applied mathematics, or related field. Working in team science. Desired Qualifications* The ideal candidate will have demonstrated experience in physical modeling of biological systems
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models. The Sutton Lab is housed within the Michigan Neuroscience Institute (https://medicine.umich.edu/dept/michigan-neuroscience-institute ) in the Interdisciplinary Taubman Biomedical Sciences Research